GxEs are complex. Tens, hundreds, even thousands of SNPs (Single Nucleotide Polymorphisms) can be significant in predicting each interaction.
Current methodologies, such as genome-wide associations (GWAS), miss so many SNPS that they cannot predict response for most GxEs.
Genteract’s new machine learning technology finds a much greater fraction of the SNPs in each GxE and generates accurate GxE predictions.
Contact us for more information, including analysis capabilities and research results,
Deliver significant cost savings for payers by decreasing prescriptions for drugs that patients won’t respond to, and recommending drugs most likely to be beneficial.
Identify genetically-defined patient subgroups who respond differently to drugs, opening up new indications for existing drugs
Identify genetically defined patient subgroups who are strong responders, enabling FDA approval of drugs that fail phase III due to lack of broad efficaciousness.
Utilize tumor and patient genomes simultaneously to select therapeutic agents most likely to produce a strong response with minimal side effects.
The clinical trial or EMR data you already have may have massive hidden value that Genteract Analysis can unlock.
Contact us now to discuss a no-obligation analysis of your data to create GxE predictions with cross-validation.